Various methods have been developed for the discernment of veins in the human body. However, improved means are needed for the rapid discernment of veins across various body types, skin colors, and topical features by persons of various medical experience levels. While infrared data systems have been utilized in the past to detect subsurface structures such as veins, bones, and other biologic materials, these systems have failed to provide sufficient resolution for the various body parts sought to be imaged.
In general, scene-based methods for low-frequency spatial noise removal and dynamic range enhancement involve removing slowly varying or low spatial frequency image content which adds little value to the visual perception of veins or other important objects found in thermal imagery in general and in medical thermal imaging in particular. These slowly varying image components may be due to anomalies within the thermal camera or they may be characteristics of the actual scene. They degrade the overall image quality and reduce the information accessible to the human observer by reducing the image dynamic range available for more valuable higher spatial frequency image content.
High spatial frequency image non-uniformity has an impact on the difficulty or ease with which veins and other important objects found in thermal imaging in general, and in medical thermal imagery in particularly, are perceived by a human observer. Noise and clutter also can have the same impact. For this reason the term spatial noise is often used to describe high spatial frequency image non-uniformity and is the term used herein.
Thus, a heretofore unaddressed need exists in the industry to address the aforementioned deficiencies and inadequacies.